The differences between declared data and observed data and how they can effectively be used to reach target audiences.
At the core of any successful audience targeting campaign is the data that is used to create a meaningful link between an offer and the needs, interests, beliefs, attitudes, and intentions of consumers.
In the world of campaign targeting, there are two main categories of targeting data: declared data and observed data.
Declared data is information that is added into databases by consumers themselves. For example, website visitors who provide name and e-mail information, consumers who take online surveys or questionnaires, and people who create social media profiles are all contributing data that can be invaluable for marketers looking for direct and relevant access to an audience based on areas of interest.
Observed data, on the other hand, is based on the identification of consumer needs and desires collected during anonymous website visits that mine each point of consumer interaction for greater insight into a visitor's needs and intentions based on how they access a website. For example, there are many different markers that site visitors leave behind when they visit a site including the time of day a site is visited, the topics of the individual pages visited, the keywords used to find sites, the total amount of time visitors spend on sites and individual pages, the technology (computer, operating system, browser, etc.) used to reach the Web pages, and IP address targeting, that may reveal geographical information about visitors.
While both declared and observed data can be effectively used to reach target audiences, there are still a large number of unknowns in either data set. For example, declared data may contain highly accurate but very limited data points - after all, unless the site has asked for specific insight, all that you know about a consumer is what they are willing to share. With observed data, the data may be largely generic as it is based on the math of big numbers and because it is largely anonymous data it can't be used as effectively for direct marketing campaigns.
At the end of the day, the goal of any digital marketer is to get the right message to the right person at the right time. But what is the best way to do this - using data you know to be accurate but that may not provide any clear intention, or data based on assumptions and the law of averages that may not be relevant?
The correct answer is "it depends."
Obviously, the effectiveness of an offer also needs to rely upon the strength of that offer, the quality of the creative, the consumer's brand-value perception, and the strength of the media buy, among other things. But good targeting starts with knowing what a target consumer wants or needs and then using any means necessary to find and reach those people.
Half the Battle: No 'One Size Fits All' Targeting Solution
Trying to sell a new collection of fashionable high-heeled shoes? Looking to sell the latest first-person shooter console game to young men between the ages of 18 and 35? Trying to sell snow removal equipment to people who are truly sick of snow?
If this is the case, using good old-fashioned demographics to reach the bulk of your audience may be a good start. After all, gender, age, and geography may be one of the central pillars of your target audience's "self-assessment" filter. But is that enough?
For example, while the vast majority of high-heeled shoes are sold to women, that doesn't mean that the vast majority of women buy high-heeled shoes. And it doesn't mean they don't already have enough shoes (although I've been informed this isn't possible…); and it definitely doesn't mean that they desire or want to buy your brand of shoes.
Bottom line: If you only have a single point of criteria for any target audience, it's a pretty good bet that you are still very far away from having a well-defined audience to go after.
There are too many tragic stories of marketers who based their campaign targeting on single criteria data like "everybody" (shudder!), gender, or even people living in the same Zip Code. While this approach may get you close to a target audience, keep in mind that getting close is the same as missing.
Instead, use as many different points of targeting criteria as you can. When working with third-party ad targeting companies, this is a very straightforward task, as most target segments are based on multiple points of criteria. However, if working in-house and certainly for planning purposes, be willing to accept the complexity of the targeting models to give you a jumping-off point to accurately define what makes your target audience uniquely yours and what it would take to bring them toward you.
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Rob Graham is the CCT (chief creative technologist) of Trainingcraft, Inc., where he heads up development of customized training programs for a wide range of digital marketing, entrepreneurial development, and digital media clients.
A 20 year veteran of digital media, Rob has served as the CEO of a multimedia development company; an interactive media strategist; a rich media production specialist; a Web analytics consultant; a corporate trainer and seminar leader; and a chief marketing officer.
When he isn't on the road presenting training workshops, Rob teaches at Harvard University, Emerson College, and the University of Massachusetts - Lowell where he teaches classes on Digital Media Development, Web Store Creation, Software Programming, Business Strategies, and Interactive Marketing Best Practices.
He is the author of "Fishing From a Barrel," a guide to using audience targeting in online advertising, and "Advertising Interactively," which explores the development and uses of rich-media-based advertising. He has been an industry columnist covering interactive marketing, digital media, and audience targeting topics since 1999.
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